This chapter represents an effort to lay out a common framework for the concepts of time to (a) support diverse researchers working on temporal aspects of learning analytics to communicate better, (b) facilitate an understanding of how different approaches to studying time in learning articulate and (c) map out the space of temporal analysis to reduce redundancy of efforts. We distinguish two concepts of time, namely the passage of time and order in time. Passage of time considers time as a continuous flow of events and order in time focuses on the organization among events. Within the passage of time we distinguish four metrics: position, duration, frequency and rate. Within order in time we discriminate between consistency, recurrent and non-recurrent change and irregular change. Metrics extracted to index passage of time can be used in many different statistical methods, whereas analysis of order in time commonly requires the usage of advanced analysis methods. For either, decisions about the level of granularity at which time is considered and segmentation of time into “windows” have important effects on analysis results. We argue that understanding the value of temporal concepts and implications for the related analysis, is foundational for closing the loop and advancing learning analytics design with temporal insights.